Soil
erodibility
(K)
refers
to
the
resistance
of
soil
erosion
and
is
an
important
factor
in
forecasting
erosion.
The
accuracy
K
determines
predictions
loss
effective
deployment
measures
for
conserving
water.
China
has
no
high-resolution
map
distribution
at
national
scale
due
uncertainty
obtaining
limitation
complex
diverse
topographic
conditions.
We
used
most
recent
soil-sampling
data
(4710
profile
points),
calculated
point-scale
using
erosion-productivity
impact
calculator
(EPIC),
random-forest
method
predict
across
by
combining
soil-landscape
relationships
environmental
variables
determined
theory
formation.
mean
predicted
was
0.035
t
ha
h
ha-1
MJ-1
mm-1,
with
a
range
from
0.015
0.061.
small
Northwest
sandstorm
region
Qinghai-Tibet
Plateau
(means
0.032
0.031,
respectively)
large
Loess
0.040
0.042,
respectively),
which
were
different
natural
geographic
conditions
soil-forming
environments
each
region.
highly
accurate,
10-fold
cross-validation
model
0.49,
root
square
error
(RMSE)
0.0077,
absolute
(MAE)
0.0059.
represented
feature
details
spatial
continuity
better
than
traditional
polygon-linking
had
higher
spatial-modeling
did
ordinary-kriging
(R2random
forest
=
0.49
>
R2ordinary
kriging
0.42).
Elevation,
solar
radiation,
wind
speed,
surface
reflectance
primary
affecting
K,
increase
(%IncMSE)
32.98,
30.69,
30.03,
28.33%,
respectively,
indicating
influence
factors
on
evolution
formation
current
physicochemical
properties.
This
study
provides
first
national-scale
China,
can
provide
basis
predicting
regional
planning
conservation
Journal of Degraded and Mining Lands Management,
Год журнала:
2024,
Номер
12(1), С. 6533 - 6544
Опубликована: Окт. 1, 2024
The
escalating
trend
of
land
degradation
poses
a
significant
challenge,
especially
in
sloping
agricultural
terrains,
driven
by
the
increasing
global
demand
for
food
and
limited
availability
flat
arable
land.
In
response
to
these
challenges,
farmers
are
compelled
shift
their
focus
towards
cultivating
terrains.
This
research
aimed
employ
comprehensive
methodology
that
integrates
on-site
field
surveys,
meticulous
laboratory
soil
analyses,
geospatial
data
mapping
erodibility.
parameters
under
scrutiny
encompass
various
crucial
aspects,
including
texture
(ranging
from
coarse
sand
very
fine
sand,
silt,
clay),
structure,
organic
matter
content,
permeability.
examination
factors
serves
as
foundation
calculating
erodibility,
utilizing
well-established
Wischmeir
Smith
formula
developed
1978.
findings
present
nuanced
understanding
erodibility
study
location,
revealing
spectrum
spanning
low
high
Specific
units,
such
Unit
1,
2,
3,
7,
9,
10,
13,
16,
exhibit
contrast,
4,
6,
14,
15
showcase
moderate
while
units
like
5,
8,
11,
12,
17,
18
characterized
moderately
These
insightful
results
shed
light
on
diverse
levels
within
studied
locations
provide
valuable
guidance
formulating
sustainable
management
practices.
Journal of Agricultural Engineering (India),
Год журнала:
2023,
Номер
60(3), С. 297 - 310
Опубликована: Окт. 9, 2023
Accurate
estimation
of
soil
loss
is
essential
for
watershed
managers
and
planners
to
identify
the
priority
areas
water
conservation
measures.
This
study
was
undertaken
estimate
average
annual
in
area
Sangli
district,
Maharashtra
by
using
Revised
Universal
Soil
Loss
Equation
(RUSLE)
conjunction
with
Geographic
Information
System
(GIS)
Remote
Sensing
(RS)
data.
The
five
potential
factors
RUSLE
impacting
erosion
were
estimated
through
remote
sensing
data,
enabling
a
comprehensive
informed
assessment
erosion.
results
analysis
revealed
that
from
varied
between
0
t.ha-1.yr-1
202.10
t.ha-1.yr-1.
Higher
western
part
area,
which
ranged
15
25
as
compared
other
parts
area.
Sangali
general,
can
be
categorised
low
district
(0-5
t.ha-1.yr-1).
generated
information
utilised
implementation
management
measures
where
there
large
under
forest
agricultural
land.
Soil
erodibility
(K)
refers
to
the
resistance
of
soil
erosion
and
is
an
important
factor
in
forecasting
erosion.
The
accuracy
K
determines
predictions
loss
effective
deployment
measures
for
conserving
water.
China
has
no
high-resolution
map
distribution
at
national
scale
due
uncertainty
obtaining
limitation
complex
diverse
topographic
conditions.
We
used
most
recent
soil-sampling
data
(4710
profile
points),
calculated
point-scale
using
erosion-productivity
impact
calculator
(EPIC),
random-forest
method
predict
across
by
combining
soil-landscape
relationships
environmental
variables
determined
theory
formation.
mean
predicted
was
0.035
t
ha
h
ha-1
MJ-1
mm-1,
with
a
range
from
0.015
0.061.
small
Northwest
sandstorm
region
Qinghai-Tibet
Plateau
(means
0.032
0.031,
respectively)
large
Loess
0.040
0.042,
respectively),
which
were
different
natural
geographic
conditions
soil-forming
environments
each
region.
highly
accurate,
10-fold
cross-validation
model
0.49,
root
square
error
(RMSE)
0.0077,
absolute
(MAE)
0.0059.
represented
feature
details
spatial
continuity
better
than
traditional
polygon-linking
had
higher
spatial-modeling
did
ordinary-kriging
(R2random
forest
=
0.49
>
R2ordinary
kriging
0.42).
Elevation,
solar
radiation,
wind
speed,
surface
reflectance
primary
affecting
K,
increase
(%IncMSE)
32.98,
30.69,
30.03,
28.33%,
respectively,
indicating
influence
factors
on
evolution
formation
current
physicochemical
properties.
This
study
provides
first
national-scale
China,
can
provide
basis
predicting
regional
planning
conservation
